v0.0.1 • In Peer Review

LocalM AiD Framework

Enterprise Architecture Principles for Governing AI-Assisted Software Development

v0.0.1 In Peer Review MPL 2.0

What Is This Framework?

LocalM™ AiD provides 27 Enterprise Architecture Principles for governing AI coding agents (GitHub Copilot, Cursor, Claude Code, etc.) and AI-assisted software development practices.

Scope: This framework defines EA Principles for governing AI-assisted software development—how AI coding tools are evaluated, configured, controlled, secured, and monitored. It is NOT about implementation timelines or solutions but specifically about foundational principles that guide governance decisions.

Notice: This framework is provided “AS IS” under the Mozilla Public License 2.0. Adapt it to your organization’s specific requirements.


Who Should Use This?

Role Use Case
Enterprise Architects Define AI governance standards
Security Teams Establish AI agent permission boundaries
Engineering Leaders Implement AI coding tool policies
Platform Engineers Configure MCP servers and agent environments
Compliance Officers Create audit trails for AI-assisted development

Core Tenets

These five tenets underpin all principles in the framework:

flowchart TB
    subgraph TENETS["LOCALM-AID CORE TENETS"]
        direction TB
        T1["HUMAN AGENCY<br/>Programmer directs; AI assists"]
        T2["STRUCTURED INTERACTION<br/>Methodology over vibe coding"]
        T3["CONTINUOUS VALIDATION<br/>Quality gates throughout"]
        T4["TRACEABILITY<br/>All interactions auditable"]
        T5["PROGRESSIVE MATURITY<br/>Grow responsibly"]

        T1 --- T2 --- T3
        T4 --- T5
    end

    style TENETS fill:#f8fafc,stroke:#6366f1,stroke-width:2px
    style T1 fill:#e0e7ff,stroke:#6366f1
    style T2 fill:#e0e7ff,stroke:#6366f1
    style T3 fill:#e0e7ff,stroke:#6366f1
    style T4 fill:#e0e7ff,stroke:#6366f1
    style T5 fill:#e0e7ff,stroke:#6366f1

Principle Structure

Every LocalM-AiD principle follows the TOGAF-aligned four-part structure:

Component Description
Name Short, memorable identifier (e.g., DM-001)
Statement Clear, declarative principle (1-2 sentences)
Rationale Business/technical justification (“why”)
Implications Consequences and requirements for adoption

Plus LocalM-AiD-specific additions:

Component Description
Maturity Alignment Requirements at Base, Medium, High levels
Governance Exception handling, compliance measures
Related Principles Cross-references within the framework

Seven Principle Categories

flowchart TB
    subgraph STRATEGY["STRATEGY & PLANNING LAYER"]
        PS["PS: Planning &<br/>Strategy (4)"]
        TSI["TSI: Tool Selection<br/>& Integration (3)"]
    end

    subgraph DEV["DEVELOPMENT LAYER"]
        TTA["TTA: Team Training<br/>& Adoption (2)"]
        DC["DC: Development<br/>& Coding (6)"]
    end

    subgraph DELIVERY["DELIVERY LAYER"]
        TQC["TQC: Testing &<br/>Quality Control (3)"]
        DM["DM: Deployment<br/>& Maintenance (2)"]
    end

    subgraph GOV["GOVERNANCE LAYER"]
        GSC["GSC: Governance, Security & Compliance (2)"]
    end

    STRATEGY --> DEV --> DELIVERY --> GOV

    style STRATEGY fill:#e3f2fd,stroke:#1976d2
    style DEV fill:#e8f5e9,stroke:#388e3c
    style DELIVERY fill:#fff3e0,stroke:#f57c00
    style GOV fill:#fce4ec,stroke:#c2185b

Total: 22 Principles

Category Code Principles Focus Area
Planning & Strategy PS 4 Strategic AI integration
Tool Selection & Integration TSI 3 AI tool ecosystem choices
Team Training & Adoption TTA 2 Human capability development
Development & Coding DC 6 AI-assisted coding practices
Testing & Quality Control TQC 3 AI quality assurance
Deployment & Maintenance DM 2 AI operations lifecycle
Governance, Security & Compliance GSC 2 AI risk management

Maturity Model

flowchart TB
    subgraph HIGH["HIGH (L3) - Advanced"]
        H["Agentic AI | Autonomous Testing | CI/CD AI<br/>Predictive Planning | Self-Healing Code"]
    end

    subgraph MEDIUM["MEDIUM (L2) - Enhanced"]
        M["AI Code Review | Structured Prompting<br/>Quality Gates | Documentation Generation"]
    end

    subgraph BASE["BASE (L1) - Foundation"]
        B["Human Review | Basic Training | Code Completion<br/>Security Scanning | Traceability"]
    end

    BASE --> MEDIUM --> HIGH

    style HIGH fill:#c8e6c9,stroke:#2e7d32
    style MEDIUM fill:#fff9c4,stroke:#f9a825
    style BASE fill:#e3f2fd,stroke:#1565c0

Legend: Each level builds on requirements of levels below

Level Name AI Autonomy Requirements
Base Foundation L1: AI-Assisted Options Mandatory for all
Medium Enhanced L2: AI-Assisted Selection Base + expanded controls
High Advanced L3: Partial Automation Medium + autonomous caps

Category Link Principle Count
All Principles View All → 22
Planning & Strategy PS Principles → 4
Tool Selection & Integration TSI Principles → 3
Team Training & Adoption TTA Principles → 2
Development & Coding DC Principles → 6
Testing & Quality Control TQC Principles → 3
Deployment & Maintenance DM Principles → 2
Governance, Security & Compliance GSC Principles → 2

Standards Alignment

LocalM-AiD principles align with established EA and AI development standards:

Standard Alignment
TOGAF Principle structure (Name, Statement, Rationale, Implications)
AGENTS.md Agent configuration principles (DC-005)
SKILL.md Capability definition standards
MCP Model Context Protocol integration (TSI)
A2A Agent-to-Agent coordination (TSI)

License